retrieve_learnings

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must convey behavioral traits. It states that the tool returns scored/ranked warnings and patterns, implying a read-only query, but it does not explicitly confirm no side effects, rate limits, or other behaviors. For a retrieval tool, this is adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loaded with the verb and resource, and every word contributes value. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of an output schema, the description provides necessary details about return content (warnings and patterns, scored/ranked). Parameter semantics are covered by the schema. The description could be improved by specifying the output format or any prerequisites, but it is largely complete for its purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning or guidance beyond what the schema already provides for each parameter (step, files, domain, components).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description explicitly states 'Retrieve relevant learnings' and specifies the output (warnings and patterns, scored/ranked). The verb and resource are clear, and the purpose is distinct from siblings like log_learning (capture) and resolve_learning (resolution).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description indicates usage 'for the current task context' but provides no explicit when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned, leaving the agent to infer appropriate usage from the context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.